I'm trying to produce this SQL with SLICK 1.0.0:
select
cat.categoryId,
cat.title,
(
select
count(product.productId)
from
products product
right join products_categories productCategory on productCategory.productId = product.productId
right join categories c on c.categoryId = productCategory.categoryId
where
c.leftValue >= cat.leftValue and
c.rightValue <= cat.rightValue
) as productCount
from
categories cat
where
cat.parentCategoryId = 2;
My most successful attempt is (I dropped the "joins" part, so it's more readable):
def subQuery(c: CategoriesTable.type) = (for {
p <- ProductsTable
} yield(p.id.count))
for {
c <- CategoriesTable
if (c.parentId === 2)
} yield(c.id, c.title, (subQuery(c).asColumn))
which produces the SQL lacking parenthesis in subquery:
select
x2.categoryId,
x2.title,
select count(x3.productId) from products x3
from
categories x2
where x2.parentCategoryId = 2
which is obviously invalid SQL Any thoughts how to have SLICK put these parenthesis in the right place? Or maybe there is a different way to achieve this?
First of all, you can put a nested SELECT within the WHERE clause with comparison operators or the IN , NOT IN , ANY , or ALL operators. The second group of operators are used when your subquery returns a list of values (rather than a single value, as in the previous example):
You can use subqueries in SELECT, INSERT, UPDATE, and DELETE statements wherever expressions are allowed. For instance, you can use a subquery as one of the column expressions in a SELECT list or as a table expression in the FROM clause. A DML statement that includes a subquery is referred to as the outer query.
Subqueries must be enclosed within parentheses. A subquery can have only one column in the SELECT clause, unless multiple columns are in the main query for the subquery to compare its selected columns. An ORDER BY command cannot be used in a subquery, although the main query can use an ORDER BY.
A subquery, also known as a nested query or subselect, is a SELECT query embedded within the WHERE or HAVING clause of another SQL query. The data returned by the subquery is used by the outer statement in the same way a literal value would be used.
I never used Slick or ScalaQuery so it was quite an adventure to find out how to achieve this. Slick is very extensible, but the documentation on extending is a bit tricky. It might already exist, but this is what I came up with. If I have done something incorrect, please correct me.
First we need to create a custom driver. I extended the H2Driver
to be able to test easily.
trait CustomDriver extends H2Driver {
// make sure we create our query builder
override def createQueryBuilder(input: QueryBuilderInput): QueryBuilder =
new QueryBuilder(input)
// extend the H2 query builder
class QueryBuilder(input: QueryBuilderInput) extends super.QueryBuilder(input) {
// we override the expr method in order to support the 'As' function
override def expr(n: Node, skipParens: Boolean = false) = n match {
// if we match our function we simply build the appropriate query
case CustomDriver.As(column, LiteralNode(name: String)) =>
b"("
super.expr(column, skipParens)
b") as ${name}"
// we don't know how to handle this, so let super hanle it
case _ => super.expr(n, skipParens)
}
}
}
object CustomDriver extends CustomDriver {
// simply define 'As' as a function symbol
val As = new FunctionSymbol("As")
// we override SimpleSql to add an extra implicit
trait SimpleQL extends super.SimpleQL {
// This is the part that makes it easy to use on queries. It's an enrichment class.
implicit class RichQuery[T: TypeMapper](q: Query[Column[T], T]) {
// here we redirect our as call to the As method we defined in our custom driver
def as(name: String) =
CustomDriver.As.column[T](Node(q.unpackable.value), name)
}
}
// we need to override simple to use our version
override val simple: SimpleQL = new SimpleQL {}
}
In order to use it we need to import specific things:
import CustomDriver.simple._
import Database.threadLocalSession
Then, to use it you can do the following (I used the tables from the official Slick documentation in my example).
// first create a function to create a count query
def countCoffees(supID: Column[Int]) =
for {
c <- Coffees
if (c.supID === supID)
} yield (c.length)
// create the query to combine name and count
val coffeesPerSupplier =
for {
s <- Suppliers
} yield (s.name, countCoffees(s.id) as "test")
// print out the name and count
coffeesPerSupplier foreach { case (name, count) =>
println(s"$name has $count type(s) of coffee")
}
The result is this:
Acme, Inc. has 2 type(s) of coffee
Superior Coffee has 2 type(s) of coffee
The High Ground has 1 type(s) of coffee
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